There is an increasing interest in multimedia applications such as video services and Voice over IP (VoIP) in the Internet, which requires higher data rates and stricter quality of service (QoS) constraints. The need for a ubiquitous access to these multimedia services is driving the evolution of cellular networks. 3GPP Long Term Evolution (LTE) was introduced to meet this ever growing demand and the increasing performance requirement for packet-based cellular broadband systems.
LTE uses orthogonal frequency division multiple access (OFDMA) in the downlink. OFDMA divides the frequency bands into a group of orthogonal subcarriers or resource block (RB) and allocates these resource blocks to users based on their requirements, system load and system configuration. Packet scheduling is responsible for the selection of users and transmission of their packets such that the radio resources are efficiently utilized and the users' QoS requirements are satisfied.
Video streaming is one of the real time (RT) services that need to be supported in the LTE system. Conventionally, to ensure that the QoS requirements of video streaming users are guaranteed, the packet loss rate (PLR) has to be kept below a threshold. Once the video decoding process starts, the packets should be received within its delay threshold; otherwise the packets are discarded and hence considered as lost packets. In this sense, granting bounded delivery delays actually means lowering packet losses. There may be a need to schedule users whose delays are becoming large but whose current channel is not the most favorable.
Due to the limited data-rate capacity of a radio-frequency channel and the time-varying nature of wireless channel, radio resource management, especially packet scheduling is crucial for wireless networks. To improve the efficiency, packet scheduling has emphasized on obtaining the required QoS while exploiting the time varying characteristics of the wireless channel by using cross-layer scheduling algorithms. Moreover, to improve performance further, there are algorithms that consider the media content.
There are many packet scheduling algorithms developed for satisfying the delay constraint requirements. These scheduling algorithms are mainly proposed for single carrier wireless systems. In these schedulers, each connection or flow is assigned a priority value based on certain criterion, and the flow with the highest priority is scheduled at each Transmission Time Interval (TTI). Scheduling algorithms designed specifically for multi-carrier wireless systems, e.g., OFDMA, are also available, but they generally require higher computational complexity.
The performances of several conventional schedulers for video streaming have been compared. In these algorithms, the QoS of the received video is measured only in terms of the packet delay, or packet loss rate. Simulation outcomes show that, in the downlink LTE system supporting video streaming services, maximum-largest weighted delay first (LD) algorithm outperforms other packet scheduling algorithms by providing a higher system throughput, supporting a higher number of users and guaranteeing fairness at a satisfactory level.
To achieve better performance, there are scheduling algorithms which consider the media content or more specifically, the video content. In these algorithms, a value of importance based on the video content is assigned to each video packet in order to account for the video perceptual quality or contribution to the distortion. The importance assignment is frame based, which does not take into the consideration of the packetization. Each video frame is usually packetized into several video packets. The packet importance is then used to determine its scheduling decision to allocate resource among the users.
The expected distortion of the received video sequence may be minimized in another algorithm. The expected distortion is used to order the video packets in the transmission queue of each user, and then gradients of the expected distortion are used to efficiently allocate resources across users. The scheduler employs a per-pixel decoder distortion estimation, which requires fully decoding of the compressed video streams.
Instead of per-pixel decoder distortion estimation, a utility function based on distortion may be used in conjunction with the gradient-based scheduling algorithm to enable content-aware resource allocation across multiple users. The utility function accounts for the dependencies between video packets and the effect that each video packet has on the final quality of the received video frame.
To avoid the decoding of video streaming before scheduling, other less complex algorithms are proposed. For example, in one of these algorithms, the position of the video frame in a group of pictures (GOP) is used to determine the importance of video packets for each user. The frame priority index (FPI) of the frame, which may be viewed as an inverse of the importance level, is simply set to be equal to the position of the frame within the GOP, i.e., the FPI for I frame is one and the FPI of the first P frame is two. The scheduling decision is then based on channel conditions, buffer emptiness, frame type and multiplexing. To have more accurate description of the video content, the motion information in the video frames may be used to determine the packet importance. The motion information may be extracted directly from the video stream without decoding of the video flow completely. However, this requires the video frames to arrive sequentially and free of errors.
Thus, there is a need to provide a packet scheduling algorithm seeking to address at least the above mentioned problems and outperform current techniques.